Global Ecology and Biodiversity

Course manual 2019/2020

Course content

Biodiversity contributes to ecosystem functioning and is of fundamental importance for human well-being. Moreover, knowledge about biodiversity and its spatial (global) distribution is essential for understanding the origin of biodiversity, for reporting and managing biodiversity change, and for contributing to the vision that biodiversity is valued, conserved, restored and wisely used, maintaining ecosystem services, sustaining a healthy planet and delivering benefits essential for all people. With this course, we want to contribute to educating a new generation of ecologists who are equipped with quantitative skills to address questions in global ecology, biodiversity and conservation science. We particularly focus on handling of large biodiversity and environmental datasets, spatial biodiversity modelling, species distribution modelling, an introduction to remote sensing products, and general tools for spatial ecological data analysis. The students will develop their own research project in global ecology and biodiversity and combine ecological and environmental data using R, Microsoft Excel/Access, Geographic Information Systems (GIS) and other quantitative tools. The statistical modelling and prediction of species potential distributions and biodiversity in geographic space is of particular focus.

Study materials

Practical training material

• Will be provided during the course

Software

• R software with various packages

• ArcGIS

• Micrososft Excel and Access

• Other tools

Other

• Powerpoint presentations and other materials will be provided

Objectives

• Design a research project in global ecology
• Find and aggregate important global datasets for exploring environmental conditions and biodiversity patterns
• Implement species distribution and ecological niche models
• Test for spatial autocorrelation in ecological data
• Apply and implement multiple regression and spatial biodiversity models
• Quantify the effect of environmental variables on species distributions and species richness

Teaching methods

• Lecture
• Laptop seminar
• Computer lab session/practical training
• Presentation/symposium
• Self-study
• Working independently on e.g. a project or thesis
• Supervision/feedback meeting

Learning activities

Attendance

This programme does not have requirements concerning attendance (TER part B).

Additional requirements for this course:

Absence needs to be communicated to the course coordinator.

Assessment

Research project (40%)
- Quality
- Theoretical knowledge
- Technical Skills
- Independence/initiative
- Original contribution
- Working attitude
- Accuracy
- Cooperation with others

Data management & curation (10%)
- Completeness
- Consistent structure
- Error free
- Good meta data

Oral presentation (10%)
- Contents
- Clarity of presentation
- Discussion

Written report (40%)
- Context
- Scientific Quality
- Use of literature
- Structure and language
- Lay-out

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Timetable

The schedule for this course is published on DataNose.

Contact information

Coordinator

• W.D. Kissling

Staff

• dr. J.R. Allan
• Zsófia Koma MSc
• dr. C. Marques Dracxler da Silva MSc
• dr. C.N.H. McMichael
• M.F. Raczka